Apparatus and method of diagnosing health by using voice

ABSTRACT

A method and apparatus for diagnosing a user&#39;s health state are provided. The apparatus includes including a voice detecting unit which detects and monitors a user&#39;s voice; a voice analyzing unit which extracts a voice feature from a voice detected by the voice detecting unit, based on a health state to be diagnosed; a voice diagnosing unit which diagnoses a health state of the user by comparing the voice feature extracted by the voice analyzing unit with an abnormal state reference, and which monitors a change in the health state; and a diagnosis outputting unit which outputs information regarding the health state and a health state change diagnosed by the voice diagnosing unit.

CROSS-REFERENCE TO RELATED PATENT APPLICATION

This application is a continuation of U.S. patent application Ser. No.13/397,744, filed on Feb. 16, 2012 in the U.S. Patent and TrademarkOffice, which claims the benefit of U.S. Provisional Patent ApplicationNo. 61/447,183, filed on Feb. 28, 2011, in the U.S. Patent and TrademarkOffice, and priority from Korean Patent Application No. 10-2011-0091316,filed on Sept. 8, 2011, in the Korean Intellectual Property Office, thedisclosures of which are incorporated herein in their entireties byreference.

BACKGROUND

1. Field

Apparatuses and methods consistent with exemplary embodiments relate toa method and apparatus for diagnosing health, and more particularly, toa method and apparatus for diagnosing states of human organs by using avoice.

2. Description of the Related Art

Recently, many people have symptoms of occipital pain and a resultantchange in voice due to environmental and lifestyle factors such as airpollution, activities in a limited space, and an increase in use ofmobile phones. If a problem associated with the occipital bone is nottreated at an early stage and thus the bone becomes deformed or there isa malignant growth, the problem may only be solved through surgery toenable a person to have a chance at recovering his/her normal voice.Thus, an early diagnosis of problems effecting the occipital bone isimportant to preserve an occipital function, and to increase rates ofsuccessful treatment and survival rates of patients.

A wide range of diseases, including Parkinson's disease can be diagnosedby using a patient's voice. Parkinson's disease is caused when cellswhich produce dopamine, which is a neurotransmitter secreted in a regionof the brain that controls movement, die, and symptoms of Parkinson'sdisease include issues including muscle rigidity, body shaking, slowedmovements, and impaired balance.

However, at a time when a person can be diagnosed based on suchsymptoms, many dopamine-producing cells have already died. Thus, inorder to improve treatment efficacy by preventing the death ofdopamine-producing cells, early diagnosis is important. A study hasproved that Parkinson's disease, which is a disease of the centralnervous system, may be diagnosed early by analyzing a patient's vocalpattern to analyze features of the vocal pattern which are difficult fora person to distinguish. The range of health diagnoses which can be madebased on such vocal analysis may be broadened.

Therefore, there is a need to provide a method and apparatus fordiagnosing states of human organs by using vocal analysis.

SUMMARY

One or more exemplary embodiments may provide a method and apparatus forchecking and diagnosing states of a patient's organs by analyzing thepatient's voice.

According to an aspect of an exemplary embodiment, there is provided ahealth diagnosing apparatus including a voice detecting unit whichdetects and monitors a user's voice; a voice analyzing unit whichextracts a voice feature from a voice detected by the voice detectingunit, based on a health state to be diagnosed; a voice diagnosing unitwhich diagnoses a health state of the user by comparing the voicefeature extracted by the voice analyzing unit with an abnormal statereference, and which monitors a change in the health state; and adiagnosis outputting unit which outputs information regarding the healthstate and a health state change diagnosed by the voice diagnosing unit.

The voice detecting unit may monitor changes in a voice state of a user.

The voice detecting unit may include an analog-to-digital converter; anda voice detecting unit which detects a voice signal from a digitalsignal output by the analog-to-digital converter.

The voice analyzing unit may include a health state selecting unit whichselects a health state type based on the voice detected by the voicedetecting unit; a voice period selecting unit which selects a voiceperiod for a diagnosis based on to the health state type selected by thehealth state selecting unit; a voice feature selecting unit whichselects a voice feature based on the health state type selected by thehealth state selecting unit; and a voice feature extracting unit whichextracts the voice feature from the voice of a user based on the voicefeature selected by the voice feature selecting unit.

The voice feature extracting unit may include a normal voice databaseand an abnormal voice database so as to distinguish between a normalvoice and an abnormal voice.

The voice diagnosing unit may include a comparing unit which comparesthe voice feature extracted by the voice analyzing unit with theabnormal state reference; a monitoring unit which detects a change overtime in a voice state of the user; and a diagnosis processing unit whichdiagnoses a state of the user's health organs according to a result ofthe comparison by the comparing unit, and a change detected by themonitoring unit.

The health diagnosing apparatus may further include a storage unit whichstores an output of the diagnosing processing unit and diagnosis timeinformation.

The diagnosis outputting unit may include a digital signal processorwhich converts information regarding the health state and a health statechange diagnosed by the voice diagnosing unit into one or more audio orvideo signals; a display unit which outputs a video signal converted bythe digital signal processor; and a speaker which outputs an audiosignal converted by the digital signal processor.

According to an aspect of another exemplary embodiment, there isprovided a method of diagnosing a user's health, the method including:detecting and monitoring a voice of the user; extracting a voice featurefrom the detected voice, based on a health state type to be diagnosed;diagnosing a health state of the user by comparing the extracted voicefeature with an abnormal state reference, and monitoring a change in thehealth state; and outputting information regarding the health state andthe health state change.

The operation of detecting the voice may include converting an inputvoice into a digital voice signal; and detecting the voice of the userfrom the digital voice signal.

The operation of extracting the voice feature may include determiningthe health state type to be diagnosed; selecting a voice period for adiagnosis according to the health state type; selecting a voice featurecorresponding to the health state type; and extracting the selectedvoice feature from the voice period.

The operation of diagnosing the health state may include analyzing achange over time in the health state ; and outputting an advisingmessage according to the change over time in the health state.

The operation of diagnosing the health state and monitoring the healthstate change may include comparing the extracted voice feature with theabnormal state reference; detecting a change over time in a voice state;and diagnosing states of the user's health according to a result of thecomparison, and the change in the voice state.

The method may further include storing and updating a result of thediagnosing and diagnosis time information in a storage unit.

The method may further include an operation of deriving references withrespect to an abnormal voice and a normal voice so as to compare thevoice feature with the abnormal state reference.

The operation of deriving the references may include operations offorming an abnormal voice database and a normal voice database;extracting an abnormal voice feature and a normal voice feature from theabnormal voice database and the normal voice database, respectively:performing comparison training with respect to the extracted abnormalvoice feature and the extracted normal voice feature; and deriving theabnormal state reference according to the comparison training.

The operation of outputting may include converting information regardingthe health state and the health state change into one or more audio orvideo signals; and outputting the one or more audio or video signals.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and/or other aspects and advantages will become more apparentby the following detailed description of exemplary embodiments withreference to the attached drawings in which:

FIG. 1 is a block diagram of a health diagnosing apparatus according toan exemplary embodiment;

FIG. 2 illustrates an example of a voice detecting unit of FIG. 1;

FIG. 3 illustrates an example of a voice analyzing unit of FIG. 1;

FIG. 4 illustrates an example of a voice diagnosing unit of FIG. 1;

FIG. 5 illustrates an example of a diagnosis outputting unit of FIG. 1;

FIG. 6 is a flowchart of a method of diagnosing health, according to anexemplary embodiment;

FIG. 7 is a detailed flowchart of a method of diagnosing health,according to another exemplary embodiment;

FIG. 8 is a detailed flowchart of a method of diagnosing health,according to another exemplary embodiment;

FIG. 9A illustrates a method of deriving references with respect to anormal voice and an abnormal voice of FIG. 6;

FIG. 9B illustrates a diagnosing reference of Gaussian Mixture Model(GMM) parameters that are modelled by two Gaussian functions;

FIG. 10 is a flowchart of a method of diagnosing health, according toanother exemplary embodiment of; and

FIG. 11 is a flowchart of a method of diagnosing a state of health byusing a mobile phone, according to an exemplary embodiment.

DETAILED DESCRIPTION

Hereinafter, exemplary embodiments will be described with reference tothe attached drawings.

As used herein, the term “and/or” includes any and all combinations ofone or more of the associated listed items.

FIG. 1 is a block diagram of a health diagnosing apparatus according toan exemplary embodiment.

The health diagnosing apparatus may be one of any number of electronicapparatuses capable of recording a voice input, or having a telephonefunction. Examples of such electronic apparatuses include a TV, a mobilephone, a smart phone, a monitor connected to a CPU, a Voice overInternet Protocol (VoIP) telephone, a portable multimedia player (PMP),a personal digital assistant (PDA), a notebook computer, or the like,but are not limited thereto.

The health diagnosing apparatus of FIG. 1 includes a voice detectingunit 110, a voice analyzing unit 120, a voice diagnosing unit 130, and adiagnosis outputting unit 140.

The voice detecting unit 110 monitors and detects a user's voice via auser's recording or a phone conversation. Also, the voice detecting unit110 additionally detects when a particular user is speaking (via thephone conversation and a voice-using game).

That is, the voice detecting unit 110 not detects when a particular useis speaking, but also constantly monitors a state of the user's voicefor any changes even when the user is not aware of the monitoring.

The voice analyzing unit 120 extracts a voice feature for each type ofhealth state from the voice detected by the voice detecting unit 110.Here, the voice analyzing unit 120 selects voice features capable ofincreasing an efficiency and performance of a diagnosis, and extractsthe voice feature in consideration of a characteristic of electronicmedical equipment that may have a limited calculation capacity and alimited memory.

The voice diagnosing unit 130 diagnoses the user's health by comparingthe voice feature extracted by the voice analyzing unit 120 with anabnormal state reference and thereby monitors changes in the state ofhealth of the user. Also, the voice diagnosing unit 130 can collect,update, and store diagnosis results.

The diagnosis outputting unit 140 converts information regarding thehealth of the user and any changes in the users state of health asdiagnosed by the voice diagnosing unit 130 into a predetermined type ofsignal, and then outputs the signal to a speaker or a monitor. Here, thepredetermined type of signal may include a graphic signal or an audioand/or a video signal.

FIG. 2 illustrates an example of the voice detecting unit 110 of FIG. 1.

The voice detecting unit 110 of FIG. 2 includes an analog-to-digitalconverter 112 and a voice detecting unit 114.

The analog-to-digital converter 112 converts an input analog signal intoa digital signal.

The voice detecting unit 114 detects a voice signal from the digitalsignal output by the analog-to-digital converter 112.

An example of a method of detecting the voice signal may include voiceactivity detection (VAD) or end point detection (EPD).

FIG. 3 illustrates an example of the voice analyzing unit 120 of FIG. 1.

The voice analyzing unit 120 of FIG. 3 includes a health state selectingunit 122, a voice period selecting unit 124, a voice feature selectingunit 126, and a voice feature extracting unit 128. The voice analyzingunit 120 may include one or more different configuring elementsaccording to a desired diagnosis function.

In order to diagnose various states of health of the user based on theuser's voice, the health state selecting unit 122 selects a type ofhealth state to be diagnosed. For example, the health state type mayinclude laryngeal cancer or Parkinson's disease.

The voice period selecting unit 124 selects a voice period of a useraccording to the health state type selected by the health stateselecting unit 122. The voice period selecting unit 124 may selectivelyselect the voice period of the user according to the selected healthstate type. For example, when laryngeal cancer is selected, only vowelportions are selected, and when the Parkinson's disease is selected, anentire sentence may be selected.

The voice feature selecting unit 126 selects a voice featurecorresponding to the health state type selected by the health stateselecting unit 122.

Exemplary, non-limiting voice features for use in distinguishing betweena normal voice and an abnormal voice are Jitter (JITT), Shimmer (SHIMM),a Harmonics-to-Noise Ratio (HNR), and a Mel-Frequency CepstralCoefficient (MFCC).

Here, JITT is an average variation of pitch, SHIMM is an averagevariation of amplitude, HNR is a ratio of a harmonic component to anoise component, and MFCC is a mathematical coefficient for soundmodeling.

Typically, an average variation of an abnormal voice pitch is greaterthan an average variation of a normal voice pitch.

Typically, an average variation of abnormal voice amplitude is greaterthan an average variation of normal voice amplitude.

Typically, a ratio of a harmonic component to a noise component in anabnormal voice is greater than a ratio of a harmonic component to anoise component in a normal voice.

In a case in which laryngeal cancer is selected, the voice feature usedto detect an abnormal voice may include JITT and SHIMM.

The voice feature extracting unit 128 extracts, from the voice of theuser, the voice feature such as JITT, SHIMM, HNR or MFCC, which isselected by the voice feature selecting unit 126. The voice featureextracting unit 128 may extract the voice feature by using software orMel-Frequency Cepstrum (MFC).

In order to distinguish between a normal voice and an abnormal voice,the voice feature extracting unit 128 includes a normal voice databaseand an abnormal voice database.

FIG. 4 illustrates an example of the voice diagnosing unit 130 of FIG.1.

The voice diagnosing unit 130 of FIG. 4 includes a comparing unit 132, adiagnosis processing unit 134, a storage unit 136, and a monitoring unit138.

The comparing unit 132 compares the voice feature extracted by the voiceanalyzing unit 120 with an abnormal state reference. Here, the abnormalstate reference is a diagnosis reference tool with which a diagnosisexpert determines the states of a user's organs by referring to anobjective voice feature. The diagnosis reference for distinguishingbetween the normal voice and the abnormal voice may be trained by usinga Gaussian Mixture Model (GMM)/a Hidden Markov Model (HMM), a neuralnetwork, or the like.

The monitoring unit 138 detects a change in the state of the user'svoice over time.

The diagnosis processing unit 134 diagnoses the states of a user'sorgans according to a result of the comparison by the comparing unit132, and any changes in the state of the user's voice as monitored bythe monitoring unit 138.

The storage unit 136 stores a result of the diagnosis performed by thediagnosis processing unit 134 and updates a diagnosis result. Thestorage unit 136 may be a magnetic recording medium such as a hard diskdrive or may be a non-volatile memory such as an electrically erasableprogrammable read-only memory (EEPROM), a flash memory, or the like, thestorage unit 136 is not limited to these examples.

FIG. 5 illustrates an example of the diagnosis outputting unit 140 ofFIG. 1.

The diagnosis outputting unit 140 of FIG. 5 includes a digital signalprocessor 142, a display unit 144, and a speaker 146.

The digital signal processor 142 converts information regarding thehealth state and any change in the health state, detected by the voicediagnosing unit 130, into audio and video signals.

The display unit 144 displays the video signal, which is processed bythe digital signal processor 142, as a graphic image or a video image.

The speaker 146 outputs the audio signal processed by the digital signalprocessor 142.

FIG. 6 is a flowchart of a method of diagnosing health, according to anexemplary embodiment.

First, a user's voice input via a recording or a phone-conversation isdetected and collected (operation 610).

With respect to each type of health state, a voice feature fordistinguishing between a normal voice and an abnormal voice is selectedfrom the collected user's voice (operation 620).

A health state is diagnosed by comparing the extracted voice featurewith an abnormal state reference, and any change in the health state ismonitored (operation 630).

Information regarding the diagnosed health state and the health statechange is output as a notice signal (operation 640).

According to the present embodiment, the states of human organs, whichcan be determined by electronic devices via sound, are diagnosed, andthe diagnosis is provided to a user, so that an early diagnosis may beperformed.

FIG. 7 is a detailed flowchart of a method of diagnosing health,according to another exemplary embodiment.

It is checked whether a user's voice has been input via a recording or aphone conversation (operation 710).

When it is determined that the user's voice has been input, a voicefeature is extracted from the input user's voice (operation 720).

A voice diagnosis is performed by comparing the extracted voice featurewith an abnormal state reference (operation 730).

In order to constantly manage a health state, a result of the voicediagnosis and voice diagnosis time information regarding the voicediagnosis are stored (operation 740). The voice diagnosis timeinformation may include a diagnosis date, a diagnosis history, or thelike.

A case in which a health state diagnosis is performed in response to auser request may be set as a one-time diagnosis.

It is checked whether a health state diagnosis is a one-time diagnosis(operation 750).

If the health state diagnosis is a one-time diagnosis, a result of thediagnosis is provided to a user, and a treatment appropriate for theresult is advised (operation 770).

If the health state diagnosis is not a one-time diagnosis, the healthstate is constantly monitored by referring to the user's voice. It isconstantly checked whether any change in the health state of the useroccurs over time (operation 760).

If a change over time occurs in the health state of the user, a resultof the diagnosis is provided to the user, and then a treatmentappropriate for the result is advised (operation 770).

FIG. 8 is a detailed flowchart of a method of diagnosing health,according to another exemplary embodiment.

It is determined whether a user's voice has been input using a recordingor a phone conversation (operation 810).

When it is determined that a user's voice has been input, a voicefeature is extracted from the input user voice (operation 820).

A voice diagnosis is performed by comparing the extracted voice featurewith an abnormal state reference (operation 830).

In order to constantly manage a health state, a result of the voicediagnosis and voice diagnosis time information regarding the voicediagnosis are stored (operation 840). The voice diagnosis timeinformation may include a voice diagnosis date, a diagnosis history, orthe like.

It is determined whether the health state diagnosis is a one-timediagnosis (operation 850).

If the health state diagnosis is a one-time diagnosis, a result of thediagnosis is provided to a user, and a treatment appropriate for theresult is advised (operation 852).

Otherwise, if the health state diagnosis is not a one-time diagnosis,the health state is constantly monitored by referring to the user'svoice, and any changes over time in the health state of the user isanalyzed (operation 860).

Then, different advising messages are displayed according to a change inthe user's health state over time.

For example, if the health state change of the user continues for one ortwo days, a message “Don't overexert yourself” is displayed to the user(operation 862), if the health state change of the user continues for atleast three days, it is determined that the user has a short-termdisease, and a message advising the user to go to see a doctor isdisplayed to the user (operation 864), and if the health state change ofthe user continues for at least two weeks, it is determined that adisease has worsened, and a message strongly advising the user to go tosee a doctor is displayed to the user (operation 866).

According to the voice diagnosis, it is determined whether a healthstate of the user has improved (operation 870).

If the health state of the user has improved, the improvement isprovided to the user (operation 880).

FIG. 9A illustrates a method of deriving references with respect to anormal voice and an abnormal voice of FIG. 6.

An abnormal voice database and a normal voice database are formed.

An abnormal voice feature and a normal voice feature are extracted fromthe abnormal voice database and the normal voice database, respectively(operations 910 and 920).

Comparison training is performed on the abnormal voice feature and thenormal voice feature by using an analysis modeling technique (operation930).

The references with respect to the normal voice and the abnormal voiceare derived via the comparison training (operation 940).

FIG. 9B illustrates a diagnosing reference with respect to a normalvoice of GMM parameters that are modeled by two Gaussian functions.

Referring to FIG. 9B, the GMM parameters including shimmer, MFCC2, andMFCC3 that are modeled by first and second Gaussian functions toindicate a division with respect to a normal voice and an abnormalvoice.

FIG. 10 is a flowchart of a method of diagnosing health, according toanother exemplary embodiment.

A user voice is input via a recording or a phone conversation (operation1010).

A voice feature with respect to an occipital state is extracted from theinput user voice (operation 1020).

The extracted voice feature is compared with an abnormal state reference(operation 1030) and then a health state with respect to the abnormalstate is automatically diagnosed (operation 1040).

The diagnosis result regarding the health state is provided to a user(operation 1050).

FIG. 11 is a flowchart of a method of diagnosing a health state by usinga mobile phone, according to an exemplary embodiment.

A phone conversation of a user is detected by the mobile phone(operation 1110).

A voice of the user during the phone conversation is detected (operation1120).

The voice of the user during the phone conversation is analyzed inreal-time, and a voice feature for diagnosing a health state isextracted from the voice of the user (operation 1130).

The heath state is analyzed using the extracted voice feature (operation1140).

A result of the diagnosis is provided to the user (operation 1150).

According to the present embodiment, when the user uses the mobilephone, the health state of the user may be automatically diagnosed byusing the voice of the user during the phone conversation. Also,whenever the user makes a phone call, the user may store and check theresult of the diagnosis.

Exemplary embodiments described herein can be written as computerprograms and can be implemented in general-use digital computers thatexecute the programs using a computer-readable recording medium.Examples of the computer-readable recording medium include magneticstorage media (e.g., ROM, floppy disks, hard disks, etc.), opticalrecording media (e.g., CD-ROMs, or DVDs), etc.

While exemplary embodiments have been particularly shown and described,it will be understood by those of ordinary skill in the art that variouschanges in form and details may be made therein without departing fromthe spirit and scope of the present inventive concept as defined by thefollowing claims.

What is claimed is:
 1. A health diagnosing apparatus comprising: a voicedetecting unit configured to detect a user's voice; a voice analyzingunit configured to extract a voice feature from the user's voicedetected by the voice detecting unit; a voice diagnosing unit configuredto diagnose the user's voice by comparing the voice feature extracted bythe voice analyzing unit with reference; a warning outputting unitconfigured to output a predetermined warning indication based on aresult of the comparing.
 2. The health diagnosing apparatus of claim 1,wherein the voice detecting unit is further configured to monitorchanges in a voice state of the user.
 3. The health diagnosing apparatusof claim 1, wherein the voice detecting unit comprises: ananalog-to-digital converter, wherein the voice detecting unit is furtherconfigured to detect a voice signal from a digital signal output by theanalog-to-digital converter.
 4. The health diagnosing apparatus of claim1, wherein the voice analyzing unit comprises: a health state selectingunit configured to select a health state type to be diagnosed based onthe user's voice detected by the voice detecting unit a voice periodselecting unit configured to select a voice period for a diagnosis basedon the health state type selected by the health state selecting unit;and a voice feature selecting unit configured to select the voicefeature according to the health state type selected by the health stateselecting unit; and a voice feature extracting unit configured toextract the voice feature from the user's voice based on the voicefeature selected by the voice feature selecting unit.
 5. The healthdiagnosing apparatus of claim 4, wherein the voice feature extractingunit comprises a normal voice database and an abnormal voice database.6. The health diagnosing apparatus of claim 1, wherein the voicediagnosing unit comprises: a comparing unit configured to compare thevoice feature extracted by the voice analyzing unit with the abnormalstate reference; a monitoring unit configured to detect a change overtime in a voice state of the user; and a diagnosis processing unitconfigured to diagnose a state of the user's health according to aresult of the comparison by the comparing unit, and the change detectedby the monitoring unit.
 7. The health diagnosing apparatus of claim 6,further comprising a storage unit configured to store an output of thediagnosing processing unit and diagnosis time information.
 8. The healthdiagnosing apparatus of claim 1, wherein the diagnosis outputting unitcomprises: a digital signal processor configured to convert informationregarding the health state and a health state change diagnosed by thevoice diagnosing unit into one or more audio or video signals; a displayunit configured to output a video signal converted by the digital signalprocessor; and a speaker configured to output an audio signal convertedby the digital signal processor.
 9. A method of diagnosing a user'shealth, the method comprising: detecting and monitoring a voice of theuser; extracting a voice feature from the detected voice; diagnosing theuser's voice by comparing the extracted voice feature with a reference;outputting a predetermined warning indication based on a result of thecomparing.
 10. The method of claim 9, wherein the detecting the voicecomprises: converting an input voice into a digital voice signal; anddetecting the voice of the user from the digital voice signal.
 11. Themethod of claim 9, wherein the extracting the voice feature comprises:determining the health state type to be diagnosed; selecting a voiceperiod for a diagnosis according to the health state type; selecting avoice feature corresponding to the health state type; and extracting theselected voice feature from the selected voice period.
 12. The method ofclaim 9, wherein the diagnosing the health state further comprises:analyzing a change over time in the health state; and outputting anadvising message according to the change over time in the health state.13. The method of claim 9, wherein the diagnosing the health state andthe monitoring the change in the health state comprise: comparing theextracted voice feature with the abnormal state reference; detecting achange over time in a voice state; and diagnosing the health state ofthe user according to a result of the comparison, and the change overtime in the voice state.
 14. The method of claim 13, further comprisingstoring and updating a result of the diagnosing and diagnosis timeinformation in a storage unit.
 15. The method of claim 13, furthercomprising determining references with respect to an abnormal voice anda normal voice.
 16. The method of claim 15, wherein the determining thereferences comprises: forming an abnormal voice database and a normalvoice database; extracting an abnormal voice feature and a normal voicefeature from the abnormal voice database and the normal voice database,respectively: performing comparison training with respect to theextracted abnormal voice feature and the extracted normal voice feature;and determining the abnormal state reference according to the comparisontraining.
 17. The method of claim 9, wherein the outputting comprises:converting information regarding the health state and the health statechange into one or more audio or video signals; and outputting the oneor more audio or video signals.
 18. A computer-readable recording mediumhaving recorded thereon a program for executing a method of diagnosing auser's health, the method comprising: detecting and monitoring a voiceof the user; extracting a voice feature from the detected voice;diagnosing the user's voice by comparing the extracted voice featurewith a reference; outputting a predetermined warning indication based ona result of the comparing.